1. Field of the Invention
Apparatuses and methods consistent with the present invention relate to context-based adaptive arithmetic coding and decoding with improved coding efficiency, and more particularly, to context-based adaptive arithmetic coding and decoding methods and apparatuses providing improved coding efficiency by initializing a context model for a given slice of an input video to a context model for a base layer slice at the same temporal position as the given slice for arithmetic coding and decoding.
2. Description of the Related Art
A video encoder performs entropy coding to convert data symbols representing video input elements into bitstreams suitably compressed for transmission or storage. The data symbols may include quantized transform coefficients, motion vectors, various headers, and the like. Examples of the entropy coding include predictive coding, variable length coding, arithmetic coding, and so on. Particularly, arithmetic coding offers the highest compression efficiency.
Successful entropy coding depends upon accurate probability models of symbols. In order to estimate a probability of symbols to be coded, context-based adaptive arithmetic coding utilizes local, spatial or temporal features. A Joint Video Team (JVT) scalable video model utilizes the context-based adaptive arithmetic coding in which probability models are adaptively updated using the symbols to be coded.
However, in order to provide for adequate coding efficiency, the context-based adaptive arithmetic coding method requires an increased number of coded blocks and accumulation of information. Thus, the conventional context-based adaptive arithmetic coding method has a drawback in that when a context model is intended to be initialized to a predefined probability model for each slice, unnecessary bits may be consumed to reach a predetermined coding efficiency after initialization.